Skill UI

This skill guides the setup and configuration of the CAST AI Workload Autoscaler, enabling dynamic right-sizing of pod resource requests (CPU and Memory). It automatically adjusts resources based on actual usage, significantly reducing cloud over-provisioning costs. Use this guide to implement workload scaling policies, configure resource limits via Kubernetes annotations, and monitor scaling events in Kubernetes environments.

This skill generates professional, customized legal agreements for 10 common business relationships, including Freelancer contracts, Partnerships, NDAs, and MSAs. Using an information-gathering wizard, it collects essential details to generate highly structured documents with type-specific clauses and plain English annotations. Ideal for formalizing complex business relationships and drafting service contracts from scratch.

A comprehensive tool for creating high-quality training datasets for custom object detection and segmentation models. It supports multiple advanced annotation methods including BBox drawing, SAM2 pixel-perfect segmentation, and DINOv3 visual grounding. Features include AI auto-detection, object tracking, and standardized COCO format export, streamlining the entire data pipeline from capture to training.

This guide provides advanced patterns for composing robust, multi-step Large Language Model (LLM) workflows using LangChain 1.0 core runnables. Learn to implement parallel retrievals (RunnableParallel), conditional routing (RunnableBranch), and state management. It also addresses common pitfalls like silent KeyErrors due to mismatched dictionary shapes, providing solutions using debug probes and type annotations for reliable RAG, classification, and extraction pipelines.

This comprehensive skill manages the entire computer vision pipeline, from custom dataset annotation to model deployment. Users can fine-tune YOLO models on proprietary COCO-formatted datasets using an agent-driven workflow. Key features include hardware-aware training (supporting CUDA, MPS, ROCm), automatic export to optimized formats (TensorRT, CoreML, OpenVINO, ONNX), and seamless, one-click deployment as an active detection skill.

Generates professional and customized Non-Disclosure Agreements (NDAs) for various business scenarios, including partnerships, hiring, and vendor relationships. It supports mutual, one-way, employee, and vendor variants, ensuring comprehensive coverage across 15 mandatory legal sections. A key feature is the inclusion of plain English annotations after each section, allowing non-legal personnel to clearly understand the agreement's terms and implications.

An advanced AI tool utilizing Meta's Segment Anything 2 (SAM2) model for interactive, pixel-perfect object segmentation. Users can click on any object within a frame or video to automatically generate precise masks. Key features include point/box prompting, video tracking across multiple frames, and seamless integration into Annotation Studio workflows, making it ideal for large-scale data labeling and video analysis pipelines.

This workflow automates the creation of step-by-step documentation guides using the TechSmith Snagit COM API and PowerShell. It first captures a series of sequential screenshots for a guide, and then uses a batch process to open and annotate these images within the Snagit Editor, ensuring consistency and efficiency in creating professional tutorials.

This guide details the architectural and implementation patterns for building modular applications or microservices using the tinystruct Java framework. It covers core concepts like using the @Action annotation for dual routing (CLI/HTTP), managing request state with Context, and using native Builder for JSON serialization, ensuring a lightweight and structured development environment.

A powerful Python skill for adding professional callouts, arrows, and labels to various images, including screenshots, diagrams, and architecture documents. It allows users to visually highlight specific areas or changes. The advanced `annotate.py` module provides algorithmic label placement, optimizing for readability and preventing overlaps. Ideal for creating clear PR descriptions, documenting changes, or building annotated demo assets.

This comprehensive skill provides a full workflow for creating high-quality, annotated animated GIFs and screen recordings. It supports capturing multi-step UI interactions using Playwright, assembling dynamic GIFs with imageio, applying variable frame timing, and adding sophisticated annotations (including fade-in effects) for clear documentation, pull request descriptions, or release note demos.

This tool converts markdown PR writeups containing unified diff blocks and severity-tagged callouts into a single, structured, 2-column HTML review document. It generates a jump-navigation, displays the diff on the left and detailed annotations on the right, and enforces a mandatory named reviewer footer, ensuring WCAG compliance.